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首页> 外文期刊>Catena: An Interdisciplinary Journal of Soil Science Hydrology-Geomorphology Focusing on Geoecology and Landscape Evolution >Fast physically-based model for rainfall-induced landslide susceptibility assessment at regional scale
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Fast physically-based model for rainfall-induced landslide susceptibility assessment at regional scale

机译:基于快速物理的降雨诱导滑坡敏感性评估在区域规模

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摘要

Rainfall-induced landslides represent an important threat in mountainous areas. Therefore, a physically-based model called "Fast Shallow Landslide Assessment Model" (FSLAM) was developed to calculate large areas (>100 km(2)) with a high-resolution topography in a very short computational time. FSLAM applies a simplified hydrological model and the infinite slope theory, while the two most sensitive soil properties regarding slope stability (cohesion and friction angle) can be stochastically included. The model has five necessary input raster files including information of soil properties, vegetation, elevation and rainfall. The principal output is the probability of failure (PoF) map. The Principality of Andorra was selected as case study, where FSLAM was successfully applied and validated using the existing landslide inventory. The PoF raster file of Andorra (including 19 million cells) was calculated in only 2 min. Therefore, an accurate calibration of the input parameters was easy, which strongly improved the final outcomes.
机译:降雨诱发的滑坡是山区的一个重要威胁。因此,开发了一个基于物理的模型,称为“快速浅层滑坡评估模型”(FSLAM),用于在极短的计算时间内计算具有高分辨率地形的大面积(>100km(2))。FSLAM采用了简化的水文模型和无限边坡理论,而关于边坡稳定性的两个最敏感的土壤特性(内聚力和摩擦角)可以随机包括在内。该模型有五个必要的输入光栅文件,包括土壤特性、植被、海拔和降雨量信息。主要输出是失效概率(PoF)图。选择安道尔公国作为案例研究,成功应用FSLAM,并使用现有滑坡清单进行验证。安道尔的PoF光栅文件(包括1900万个单元格)只需2分钟即可计算出来。因此,输入参数的精确校准很容易,这大大改善了最终结果。

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